• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

视觉搜索中的决策过程作为目标出现概率的函数。

Decision processes in visual search as a function of target prevalence.

作者信息

Peltier Chad, Becker Mark W

机构信息

Department of Psychology, Michigan State University.

出版信息

J Exp Psychol Hum Percept Perform. 2016 Sep;42(9):1466-76. doi: 10.1037/xhp0000248. Epub 2016 May 5.

DOI:10.1037/xhp0000248
PMID:27149294
Abstract

The probability of missing a target increases in low target prevalence search tasks. Wolfe and Van Wert (2010) propose 2 causes of this effect: reducing the quitting threshold, and conservatively shifting the decision making criterion used to evaluate each item. Reducing the quitting threshold predicts that target absent responses will be made without fully inspecting the display, increasing misses due to never inspecting the target (selection errors). The shift in decision criterion increases the likelihood of failing to recognize an inspected target (identification errors). Though there is robust evidence that target prevalence rates shift quitting thresholds, the proposed shift in decision making criterion has little support. In Experiment 1 we eye-tracked participants during searches of high, medium, and low prevalence. Eye movements were used to classify misses as selection or identification errors. Identification errors increased as prevalence decreased, supporting the claim that decision criterion becomes more conservative as prevalence decreases. In addition, as prevalence decreased, the dwell time on targets increased while dwell times on distractors decreased. We propose that the effect of prevalence on decision making for individual items is best modeled as a shift in criterion in a drift diffusion model, rather than signal detection, as drift diffusion accounts for this pattern of decision times. In Experiment 2 we replicate these findings while presenting stimuli in an rapid serial visual presentation (RSVP) stream. Experiments 1 and 2 were consistent with the conclusion that prevalence rate influences the item-by-item decision criterion, and are consistent with a drift diffusion model of this decision process. (PsycINFO Database Record

摘要

在低目标出现率的搜索任务中,错过目标的概率会增加。沃尔夫和范·韦特(2010年)提出了造成这种效应的两个原因:降低停止阈值,以及保守地改变用于评估每个项目的决策标准。降低停止阈值预示着在没有充分检查显示的情况下就会做出目标不存在的反应,这会因从未检查目标(选择错误)而增加漏报情况。决策标准的改变增加了未能识别已检查目标的可能性(识别错误)。尽管有确凿证据表明目标出现率会改变停止阈值,但所提出的决策标准的改变却几乎没有得到支持。在实验1中,我们在高、中、低出现率的搜索过程中对参与者进行了眼动追踪。眼动被用来将漏报分类为选择错误或识别错误。随着出现率的降低,识别错误增加,这支持了随着出现率降低决策标准会变得更加保守的观点。此外,随着出现率降低,对目标的注视时间增加,而对干扰项的注视时间减少。我们提出,出现率对单个项目决策的影响最好被建模为漂移扩散模型中标准的改变,而不是信号检测,因为漂移扩散模型能够解释这种决策时间模式。在实验2中,我们在快速序列视觉呈现(RSVP)流中呈现刺激时重复了这些发现。实验1和实验2都与出现率影响逐个项目的决策标准这一结论一致,并且与该决策过程的漂移扩散模型一致。(《心理学文摘数据库记录》 )

相似文献

1
Decision processes in visual search as a function of target prevalence.视觉搜索中的决策过程作为目标出现概率的函数。
J Exp Psychol Hum Percept Perform. 2016 Sep;42(9):1466-76. doi: 10.1037/xhp0000248. Epub 2016 May 5.
2
Failures of perception in the low-prevalence effect: Evidence from active and passive visual search.低患病率效应中的感知失败:来自主动和被动视觉搜索的证据。
J Exp Psychol Hum Percept Perform. 2015 Aug;41(4):977-94. doi: 10.1037/xhp0000053. Epub 2015 Apr 27.
3
Evidence for top-down control of eye movements during visual decision making.视觉决策过程中眼动自上而下控制的证据。
J Vis. 2010 May 1;10(5):15. doi: 10.1167/10.5.15.
4
Introspection during visual search.视觉搜索过程中的内省。
Conscious Cogn. 2014 Oct;29:212-29. doi: 10.1016/j.concog.2014.08.009. Epub 2014 Oct 3.
5
Working Memory Capacity Predicts Selection and Identification Errors in Visual Search.工作记忆容量可预测视觉搜索中的选择和识别错误。
Perception. 2017 Jan;46(1):109-115. doi: 10.1177/0301006616678421. Epub 2016 Nov 19.
6
Object-scene relationships vary the magnitude of target prevalence effects in visual search.物体-场景关系会改变视觉搜索中目标流行效应的大小。
J Exp Psychol Hum Percept Perform. 2016 Jun;42(6):766-75. doi: 10.1037/xhp0000183. Epub 2015 Nov 30.
7
A little bit of history repeating: Splitting up multiple-target visual searches decreases second-target miss errors.历史重演:将多目标视觉搜索分开进行可减少对第二个目标的漏报错误。
J Exp Psychol Appl. 2014 Jun;20(2):112-25. doi: 10.1037/xap0000014. Epub 2014 Apr 7.
8
Target-to-distractor ratio effects on decision time in the orderly array shape cancellation task.在有序阵列形状删除任务中,目标与干扰项比例对决策时间的影响。
Psychol Rep. 2013 Oct;113(2):353-61. doi: 10.2466/15.03.PR0.113x24z2.
9
Decision-making training reduces the attentional blink.决策训练可减少注意瞬脱。
J Exp Psychol Hum Percept Perform. 2018 Feb;44(2):195-205. doi: 10.1037/xhp0000454. Epub 2017 May 29.
10
Colour and spatial cueing in low-prevalence visual search.低患病率视觉搜索中的颜色和空间线索提示
Q J Exp Psychol (Hove). 2012;65(7):1327-44. doi: 10.1080/17470218.2012.656662. Epub 2012 Apr 12.

引用本文的文献

1
Presenting segmented images in a rapid serial visual presentation stream improves search accuracy.在快速序列视觉呈现流中展示分割图像可提高搜索准确性。
Cogn Res Princ Implic. 2025 Aug 15;10(1):49. doi: 10.1186/s41235-025-00653-2.
2
The joint effect of feedback order and reward schemes on prevalence-induced perceptual decisions.反馈顺序和奖励机制对患病率诱导的感知决策的联合影响。
Sci Rep. 2025 Jul 10;15(1):24908. doi: 10.1038/s41598-025-10707-6.
3
Salient distractors influence information accrual rather than quitting threshold in visual search.
显著干扰项在视觉搜索中影响信息积累而非终止阈值。
Atten Percept Psychophys. 2025 Jul;87(5):1458-1470. doi: 10.3758/s13414-025-03104-8. Epub 2025 Jun 16.
4
Mixing it up: Intermixed and blocked visual search tasks produce similar results.混合操作:混合式和分块式视觉搜索任务产生相似的结果。
Atten Percept Psychophys. 2025 May 8. doi: 10.3758/s13414-025-03077-8.
5
Cue relevance drives early quitting in visual search.线索关联驱动视觉搜索中的早期放弃。
Cogn Res Princ Implic. 2024 Aug 26;9(1):54. doi: 10.1186/s41235-024-00587-1.
6
Effects of machine learning errors on human decision-making: manipulations of model accuracy, error types, and error importance.机器学习错误对人类决策的影响:模型精度、错误类型和错误重要性的操纵。
Cogn Res Princ Implic. 2024 Aug 26;9(1):56. doi: 10.1186/s41235-024-00586-2.
7
The label-feedback effect is influenced by target category in visual search.标签反馈效应在视觉搜索中受目标类别影响。
PLoS One. 2024 Aug 1;19(8):e0306736. doi: 10.1371/journal.pone.0306736. eCollection 2024.
8
Activation thresholds, not quitting thresholds, account for the low prevalence effect in dynamic search.激活阈值而非退出阈值,解释了动态搜索中的低流行率效应。
Atten Percept Psychophys. 2024 Nov;86(8):2589-2603. doi: 10.3758/s13414-024-02919-1. Epub 2024 Jul 8.
9
Activated long-term memory and visual working memory during hybrid visual search: Effects on target memory search and distractor memory.混合视觉搜索过程中激活的长时记忆和视觉工作记忆:对目标记忆搜索和分心物记忆的影响。
Mem Cognit. 2024 Nov;52(8):2156-2171. doi: 10.3758/s13421-024-01556-1. Epub 2024 Mar 25.
10
Determinants of Face Recognition: The Role of Target Prevalence and Similarity.人脸识别的决定因素:目标普遍性和相似度的作用。
J Cogn. 2024 Feb 21;7(1):27. doi: 10.5334/joc.339. eCollection 2024.